Pitcher Precision
Sasank Vishnubhatla
4/17/2019
Last Update: 2019-05-03 10:16:34
Libraries
Let’s load some libraries in first.
library(baseballr)
library(pitchRx)
library(tidyverse)Let’s also clean out environment.
rm(list = ls())With these libraries, we can get out data as well as visaulize it. Let’s take a look at some players to see what we can look at.
Data Loading
Here are the list of players I will be looking at.
- Noah Syndergaard - Player ID: 592789
- Patrick Corbin - Player ID: 571578
- Felipe Vazquez - Player ID: 553878
- Marcus Stroman - Player ID: 573186
- Justin Verlander - Player ID: 434378
- Blake Treinen - Player ID: 595014
Let’s now scrape the data for each player.
scrape.data = function(start, id) {
data = scrape_statcast_savant(start_date = start,
end_date = format(Sys.time(), "%Y-%m-%d"),
playerid = id,
player_type = 'pitcher')
data
}
start = "2019-01-01"
syndergaard.data = scrape.data(start, 592789)
corbin.data = scrape.data(start, 571578)
vazquez.data = scrape.data(start, 553878)
stroman.data = scrape.data(start, 573186)
verlander.data = scrape.data(start, 434378)
treinen.data = scrape.data(start, 595014)Now with our data, let’s get the information we want out of it.
filter.data = function(data) {
filtered = data.frame(name = data %>% pull(player_name),
pitch = data %>% pull(pitch_type),
outcome = data %>% pull(type),
date = data %>% pull(game_date),
event = data %>% pull(events),
descrip = data %>% pull(description),
xcoord = data %>% pull(plate_x),
ycoord = data %>% pull(plate_z),
xmove = data %>% pull(pfx_x),
ymove = data %>% pull(pfx_z),
velo = data %>% pull(effective_speed),
spin = data %>% pull(release_spin_rate),
exvelo = data %>% pull(launch_speed),
exang = data %>% pull(launch_angle),
year = substring(data %>% pull(game_date), 0, 4))
filtered
}
syndergaard = filter.data(syndergaard.data)
corbin = filter.data(corbin.data)
stroman = filter.data(stroman.data)
treinen = filter.data(treinen.data)
vazquez = filter.data(vazquez.data)
verlander = filter.data(verlander.data)With this filtered data, we have selected the following columns:
- Name
- Pitch type
- Pitch outcome (Strike, Ball, In play)
- Game Date
- Event
- Description of event
- X coordinate (horizontal location) of pitch
- Y coordinate (vertical location) of pitch
- Horizontal movement (X coordinate movement) of pitch
- Vertical movement (Y coordinate movement) of pitch
- Velocity of pitch
- Spin rate of pitch
- Exit velocity of pitch
- Launch angle of pitch
Visualization
Let’s start visualizing some of this data. Before that, let me define a strikezone. This strikezone was taken from the website Baseball with R
topKzone = 3.5
botKzone = 1.6
inKzone = -.95
outKzone = 0.95
kZone = data.frame(x = c(inKzone, inKzone, outKzone, outKzone, inKzone),
y = c(botKzone, topKzone, topKzone, botKzone, botKzone))Pitch Location via Outcome
Let’s look at pitch location with if the pitch is a ball or strike. We know X is hit into play, B is ball, and S is any type of strike.
graph.pitch.heatmap.out = function(player) {
graph = ggplot(player) +
geom_jitter(aes(x = player$xcoord,
y = player$ycoord,
color = player$outcome)) +
xlab("Horizontal Position") +
ylab("Vertical Position") +
ggtitle(paste(player$name[1], "Heatmap", sep = " ")) +
labs(color = "Pitch Outcome") +
theme_minimal() + geom_path(aes(x, y), data = kZone)
graph
}
corbin.heatmap.out = graph.pitch.heatmap.out(corbin)
corbin.heatmap.out
stroman.heatmap.out = graph.pitch.heatmap.out(stroman)
stroman.heatmap.out
syndergaard.heatmap.out = graph.pitch.heatmap.out(syndergaard)
syndergaard.heatmap.out## Warning: Removed 1 rows containing missing values (geom_point).
treinen.heatmap.out = graph.pitch.heatmap.out(treinen)
treinen.heatmap.out## Warning: Removed 23 rows containing missing values (geom_point).
vazquez.heatmap.out = graph.pitch.heatmap.out(vazquez)
vazquez.heatmap.out
verlander.heatmap.out = graph.pitch.heatmap.out(verlander)
verlander.heatmap.out
Pitch Location via Pitch Type
Let’s look at pitch location via pitch type.
graph.pitch.heatmap.type = function(player) {
graph = ggplot(player) +
geom_jitter(aes(x = player$xcoord,
y = player$ycoord,
color = player$pitch)) +
xlab("Horizontal Position") +
ylab("Vertical Position") +
ggtitle(paste(player$name[1], "Heatmap", sep = " ")) +
labs(color = "Pitch Type") +
theme_minimal() + geom_path(aes(x, y), data = kZone)
graph
}
corbin.heatmap.type = graph.pitch.heatmap.type(corbin)
corbin.heatmap.type
stroman.heatmap.type = graph.pitch.heatmap.type(stroman)
stroman.heatmap.type
syndergaard.heatmap.type = graph.pitch.heatmap.type(syndergaard)
syndergaard.heatmap.type## Warning: Removed 1 rows containing missing values (geom_point).
treinen.heatmap.type = graph.pitch.heatmap.type(treinen)
treinen.heatmap.type## Warning: Removed 23 rows containing missing values (geom_point).
vazquez.heatmap.type = graph.pitch.heatmap.type(vazquez)
vazquez.heatmap.type
verlander.heatmap.type = graph.pitch.heatmap.type(verlander)
verlander.heatmap.type
Pitch Location via Velocity
Let’s look at pitch location via velocity.
graph.pitch.heatmap.velo = function(player) {
graph = ggplot(player) +
geom_jitter(aes(x = player$xcoord,
y = player$ycoord,
color = player$velo)) +
xlab("Horizontal Position") +
ylab("Vertical Position") +
ggtitle(paste(player$name[1], "Heatmap", sep = " ")) +
labs(color = "Velocity") +
scale_color_gradient(low = "blue", high = "red") +
theme_minimal() + geom_path(aes(x, y), data = kZone)
graph
}
corbin.heatmap.velo = graph.pitch.heatmap.velo(corbin)
corbin.heatmap.velo
stroman.heatmap.velo = graph.pitch.heatmap.velo(stroman)
stroman.heatmap.velo
syndergaard.heatmap.velo = graph.pitch.heatmap.velo(syndergaard)
syndergaard.heatmap.velo## Warning: Removed 1 rows containing missing values (geom_point).
treinen.heatmap.velo = graph.pitch.heatmap.velo(treinen)
treinen.heatmap.velo## Warning: Removed 23 rows containing missing values (geom_point).
vazquez.heatmap.velo = graph.pitch.heatmap.velo(vazquez)
vazquez.heatmap.velo
verlander.heatmap.velo = graph.pitch.heatmap.velo(verlander)
verlander.heatmap.velo
Pitch Movement
To view the movement, let’s just determine the average movement for each type of pitch that each player has. First let’s make a few helpful functions for us.
graph.pitch.xmovement = function(player) {
graph = ggplot(player) +
geom_boxplot(aes(x = player$pitch,
y = player$xmove,
color = player$pitch)) +
coord_flip() +
labs(color = "Pitch Type") +
xlab("Pitch Type") + ylab("Horizontal Movement") +
ggtitle(paste(player$name[1], "Horizontal Movement", sep = " ")) +
theme_minimal()
}
graph.pitch.ymovement = function(player) {
graph = ggplot(player) +
geom_boxplot(aes(x = player$pitch,
y = player$ymove,
color = player$pitch)) +
labs(color = "Pitch Type") +
xlab("Pitch Type") + ylab("Vertical Movement") +
ggtitle(paste(player$name[1], "Vertical Movement", sep = " ")) +
theme_minimal()
}Patrick Corbin
corbin.xmove = graph.pitch.xmovement(corbin)
corbin.ymove = graph.pitch.ymovement(corbin)
corbin.xmove
corbin.ymove
Marcus Stroman
stroman.xmove = graph.pitch.xmovement(stroman)
stroman.ymove = graph.pitch.ymovement(stroman)
stroman.xmove
stroman.ymove
Noah Syndergaard
syndergaard.xmove = graph.pitch.xmovement(syndergaard)
syndergaard.ymove = graph.pitch.ymovement(syndergaard)
syndergaard.xmove## Warning: Removed 1 rows containing non-finite values (stat_boxplot).
syndergaard.ymove## Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Blake Treinen
treinen.xmove = graph.pitch.xmovement(treinen)
treinen.ymove = graph.pitch.ymovement(treinen)
treinen.xmove## Warning: Removed 23 rows containing non-finite values (stat_boxplot).
treinen.ymove## Warning: Removed 23 rows containing non-finite values (stat_boxplot).
Felipe Vazquez
vazquez.xmove = graph.pitch.xmovement(vazquez)
vazquez.ymove = graph.pitch.ymovement(vazquez)
vazquez.xmove
vazquez.ymove
Justin Verlander
verlander.xmove = graph.pitch.xmovement(verlander)
verlander.ymove = graph.pitch.ymovement(verlander)
verlander.xmove
verlander.ymove
Pitch Velocity
We need to separate each pitch first by type. Then we can see how the pitch’s velocity changed over time.
graph.pitch.velo = function(player) {
graph = ggplot(player) +
geom_line(aes(x = 1:length(player$velo),
y = player$velo,
color = player$pitch)) +
xlab("Pitches Thrown") + ylab("Velocity") + labs(color = "Pitch Type") +
ggtitle(paste(player$name[1], "Pitch Velocity Chart", sep = " ")) +
theme_minimal()
}
corbin.velo = graph.pitch.velo(corbin)
corbin.velo
stroman.velo = graph.pitch.velo(stroman)
stroman.velo
syndergaard.velo = graph.pitch.velo(syndergaard)
syndergaard.velo## Warning: Removed 1 rows containing missing values (geom_path).
treinen.velo = graph.pitch.velo(treinen)
treinen.velo## Warning: Removed 23 rows containing missing values (geom_path).
vazquez.velo = graph.pitch.velo(vazquez)
vazquez.velo
verlander.velo = graph.pitch.velo(verlander)
verlander.velo
Pitch Spin Rate
graph.pitch.spin = function(player) {
graph = ggplot(player) +
geom_step(aes(x = 1:length(player$spin),
y = player$spin,
color = player$pitch),
direction = "vh") +
xlab("Pitches Thrown") + ylab("Spin Rate") + labs(color = "Pitch Type") +
ggtitle(paste(player$name[1], "Pitch Spin Rate Chart", sep = " ")) +
theme_minimal()
}
corbin.spin = graph.pitch.spin(corbin)
corbin.spin
stroman.spin = graph.pitch.spin(stroman)
stroman.spin
syndergaard.spin = graph.pitch.spin(syndergaard)
syndergaard.spin## Warning: Removed 1 rows containing missing values (geom_path).
treinen.spin = graph.pitch.spin(treinen)
treinen.spin## Warning: Removed 23 rows containing missing values (geom_path).
vazquez.spin = graph.pitch.spin(vazquez)
vazquez.spin
verlander.spin = graph.pitch.spin(verlander)
verlander.spin
Analysis
I’ll be looking at a few specific Pittsburgh Pirates pitchers and looking at them from year to year.
Jameson Taillon
Let’s first read in our data for Taillon.
taillon.data = scrape.data("2018-01-01", 592791)## 2018-01-01 is not a date. Attempting to coerce...## https://baseballsavant.mlb.com/statcast_search/csv?all=true&hfPT=&hfAB=&hfBBT=&hfPR=&hfZ=&stadium=&hfBBL=&hfNewZones=&hfGT=R%7CPO%7CS%7C&hfC&hfSea=2018%7C&hfSit=&hfOuts=&opponent=&pitcher_throws=&batter_stands=&hfSA=&player_type=pitcher&hfInfield=&team=&position=&hfOutfield=&hfRO=&home_road=&pitchers_lookup%5B%5D=592791&game_date_gt=2018-01-01&game_date_lt=2019-05-03&hfFlag=&hfPull=&metric_1=&hfInn=&min_pitches=0&min_results=0&group_by=name&sort_col=pitches&player_event_sort=h_launch_speed&sort_order=desc&min_abs=0&type=details## These data are from BaseballSevant and are property of MLB Advanced Media, L.P. All rights reserved.## Grabbing data, this may take a minute...## URL read and payload acquired successfully.taillon = filter.data(taillon.data)Now, let’s just get some averages of Taillon’s pitches.
taillon.ff = taillon[taillon$pitch == "FF",]
taillon.ft = taillon[taillon$pitch == "FT",]
taillon.sl = taillon[taillon$pitch == "SL",]
taillon.cu = taillon[taillon$pitch == "CU",]
taillon.ch = taillon[taillon$pitch == "CH",]
taillon.ff = taillon.ff[complete.cases(taillon.ff),]
taillon.ft = taillon.ff[complete.cases(taillon.ft),]
taillon.sl = taillon.ff[complete.cases(taillon.sl),]
taillon.cu = taillon.ff[complete.cases(taillon.cu),]
taillon.ch = taillon.ff[complete.cases(taillon.ch),]| Pitch | Average Velocity | Standard Deviation of Velocity | Average Spin Rate |
|---|---|---|---|
| 4-Seam Fastball | 95.4522176 | 1.0237036 | 2355.1823529 |
| 2-Seam Fastball | NA | NA | NA |
| Slider | NA | NA | NA |
| Curveball | NA | NA | NA |
| Changeup | 95.62225 | 0.936624 | 2356.7857143 |
Now let’s make some graphs.
taillon.heatmap.out = graph.pitch.heatmap.out(taillon)
taillon.heatmap.out
taillon.heatmap.type = graph.pitch.heatmap.type(taillon)
taillon.heatmap.type
taillon.heatmap.velo = graph.pitch.heatmap.velo(taillon)
taillon.heatmap.velo
taillon.spin = graph.pitch.spin(taillon)
taillon.spin
taillon.velo = graph.pitch.velo(taillon)
taillon.velo
taillon.xmove = graph.pitch.xmovement(taillon)
taillon.xmove
taillon.ymove = graph.pitch.ymovement(taillon)
taillon.ymove
Richard Rodriguez
rodriguez.data = scrape.data("2018-01-01", 593144)## 2018-01-01 is not a date. Attempting to coerce...## https://baseballsavant.mlb.com/statcast_search/csv?all=true&hfPT=&hfAB=&hfBBT=&hfPR=&hfZ=&stadium=&hfBBL=&hfNewZones=&hfGT=R%7CPO%7CS%7C&hfC&hfSea=2018%7C&hfSit=&hfOuts=&opponent=&pitcher_throws=&batter_stands=&hfSA=&player_type=pitcher&hfInfield=&team=&position=&hfOutfield=&hfRO=&home_road=&pitchers_lookup%5B%5D=593144&game_date_gt=2018-01-01&game_date_lt=2019-05-03&hfFlag=&hfPull=&metric_1=&hfInn=&min_pitches=0&min_results=0&group_by=name&sort_col=pitches&player_event_sort=h_launch_speed&sort_order=desc&min_abs=0&type=details## These data are from BaseballSevant and are property of MLB Advanced Media, L.P. All rights reserved.## Grabbing data, this may take a minute...## URL read and payload acquired successfully.rodriguez = filter.data(rodriguez.data)Joe Musgrove
musgrove.data = scrape.data("2018-01-01", 605397)## 2018-01-01 is not a date. Attempting to coerce...## https://baseballsavant.mlb.com/statcast_search/csv?all=true&hfPT=&hfAB=&hfBBT=&hfPR=&hfZ=&stadium=&hfBBL=&hfNewZones=&hfGT=R%7CPO%7CS%7C&hfC&hfSea=2018%7C&hfSit=&hfOuts=&opponent=&pitcher_throws=&batter_stands=&hfSA=&player_type=pitcher&hfInfield=&team=&position=&hfOutfield=&hfRO=&home_road=&pitchers_lookup%5B%5D=605397&game_date_gt=2018-01-01&game_date_lt=2019-05-03&hfFlag=&hfPull=&metric_1=&hfInn=&min_pitches=0&min_results=0&group_by=name&sort_col=pitches&player_event_sort=h_launch_speed&sort_order=desc&min_abs=0&type=details## These data are from BaseballSevant and are property of MLB Advanced Media, L.P. All rights reserved.## Grabbing data, this may take a minute...## URL read and payload acquired successfully.musgrove = filter.data(musgrove.data)Jordan Lyles
lyles.data = scrape.data("2018-01-01", 543475)## 2018-01-01 is not a date. Attempting to coerce...## https://baseballsavant.mlb.com/statcast_search/csv?all=true&hfPT=&hfAB=&hfBBT=&hfPR=&hfZ=&stadium=&hfBBL=&hfNewZones=&hfGT=R%7CPO%7CS%7C&hfC&hfSea=2018%7C&hfSit=&hfOuts=&opponent=&pitcher_throws=&batter_stands=&hfSA=&player_type=pitcher&hfInfield=&team=&position=&hfOutfield=&hfRO=&home_road=&pitchers_lookup%5B%5D=543475&game_date_gt=2018-01-01&game_date_lt=2019-05-03&hfFlag=&hfPull=&metric_1=&hfInn=&min_pitches=0&min_results=0&group_by=name&sort_col=pitches&player_event_sort=h_launch_speed&sort_order=desc&min_abs=0&type=details## These data are from BaseballSevant and are property of MLB Advanced Media, L.P. All rights reserved.## Grabbing data, this may take a minute...## URL read and payload acquired successfully.lyles = filter.data(lyles.data)Kyle Crick
crick.data = scrape.data("2018-01-01", 605195)## 2018-01-01 is not a date. Attempting to coerce...## https://baseballsavant.mlb.com/statcast_search/csv?all=true&hfPT=&hfAB=&hfBBT=&hfPR=&hfZ=&stadium=&hfBBL=&hfNewZones=&hfGT=R%7CPO%7CS%7C&hfC&hfSea=2018%7C&hfSit=&hfOuts=&opponent=&pitcher_throws=&batter_stands=&hfSA=&player_type=pitcher&hfInfield=&team=&position=&hfOutfield=&hfRO=&home_road=&pitchers_lookup%5B%5D=605195&game_date_gt=2018-01-01&game_date_lt=2019-05-03&hfFlag=&hfPull=&metric_1=&hfInn=&min_pitches=0&min_results=0&group_by=name&sort_col=pitches&player_event_sort=h_launch_speed&sort_order=desc&min_abs=0&type=details## These data are from BaseballSevant and are property of MLB Advanced Media, L.P. All rights reserved.## Grabbing data, this may take a minute...## URL read and payload acquired successfully.crick = filter.data(crick.data)